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We rely on polymer foams to build things from tissue engineer scaffold to airplanes. Still, traditional polymer foaming methods usually involve chemical agents or high-pressure gases, which can cause environmental and safety concerns. Therefore, we developed a novel microwave foaming method that uses only microwave irradiation as the driving force of foaming and water as the blowing agent. Using the microwave foaming method, we managed to generate polymer foams based on polyvinyl alcohol (PVA) within minutes. We also conducted experiments to study the influence of processing parameters on cell structures, such as the influence of microwave power and the initial water content, which shows that this method is controllable and has the potential to replace traditional foaming methods in future industrial application scenarios.

Graph similarity computation aims to predict a similarity score between one pair of graphs to facilitate downstream applications, such as finding the most similar chemical compounds similar to a query compound or Fewshot 3D Action Recognition. Recently, some graph similarity computation models based on neural networks have been proposed, which are either based on graph-level interaction or node-level comparison. However, when the number of nodes in the graph increases, it will inevitably bring about reduced representation ability or high computation cost. Motivated by this observation, we propose a graph partitioning and graph neural network-based model, called PSimGNN, to effectively resolve this issue. Specifically, each of the input graphs is partitioned into a set of subgraphs to extract the local structural features directly. Next, a novel graph neural network with an attention mechanism is designed to map each subgraph into an embedding vector. Some of these subgraph pairs are automatically selected for node-level comparison to supplement the subgraph-level embedding with fine-grained information. Finally, coarse-grained interaction information among subgraphs and fine-grained comparison information among nodes in different subgraphs are integrated to predict the final similarity score. Experimental results on graph datasets with different graph sizes demonstrate that PSimGNN outperforms state-of-the-art methods in graph similarity computation tasks using approximate Graph Edit Distance (GED) as the graph similarity metric.

Patterning high-resolution microstructures on thermoplastic substrates is of fundamental importance for the commercialization of microfluidics, advanced functional surfaces, and optical elements. Though many methods are developed to fabricate micropatterned plastic devices with 100 μm resolution, they suffer substantially higher cost or lower productivity when the resolution of the micropatterns is to be further improved. Here, we develop low-cost molds consisting of thin ceramic-filled-epoxy composite coatings on steel substrates. By virtue of the loaded ZrO

Artificial intelligence (AI) is an emerging technology with great potential, and its robust calculation and analysis capabilities are unmatched by traditional calculation tools. With the promotion of deep learning and open-source platforms, the threshold of AI has also become lower. Combining artificial intelligence with traditional fields to create new fields of high research and application value has become a trend. AI has been involved in many disciplines, such as medicine, materials, energy, and economics. The development of AI requires the support of many kinds of data, and microfluidic systems can often mine object data on a large scale to support AI. Due to the excellent synergy between the two technologies, excellent research results have emerged in many fields. In this review, we briefly review AI and microfluidics and introduce some applications of their combination, mainly in nanomedicine and material synthesis. Finally, we discuss the development trend of the combination of the two technologies.

Rectangular microchannels are useful in biological and chemical research. However, high-efficient method for producing rectangular microchannels has not been established. Here, flexible rectangular...

Step emulsification is a low-shear method to produce monodispersed microdroplets by spontaneous breakup of dispersed fluid at a spatial "step". As a semi-open microfluidic system, controllable coalescence of multiple components in step emulsification has not been achieved. Here, we use a low voltage to control the coalescence position of flow tips in the terrace. By investigating the interaction between the coalescence behavior and the hydrodynamics of the drop formation, we numerically predict the shape evolution of the flow tips and give a semi-empirical model to calculate the sizes of droplets by the flow rates and the voltage. Furthermore, we explore the capabilities of the electro-coalescer based on step emulsification. To trigger the coalescence in the wide reservoir, the clogging problem in precipitate-producing reactions is avoided. Besides, the low-shear nature of step emulsification also facilitates the production of multilayered droplets.

In recent years, multivariate time-series classification (MTSC) has attracted considerable attention owing to the advancement of sensing technology. Existing deep-learning-based MTSC techniques, which mostly rely on convolutional or recurrent neural networks, focus primarily on the temporal dependency of a single time series. Based on this, complex pairwise dependencies among multivariate variables can be better described using advanced graph methods, where each variable is regarded as a node in the graph, and their dependencies are regarded as edges. Furthermore, current spatial-temporal modeling (e.g., graph classification) methodologies based on graph neural networks (GNNs) are inherently flat and cannot hierarchically aggregate node information. To address these limitations, we propose a novel graph-pooling-based framework, MTPool, to obtain an expressive global representation of MTS. We first convert MTS slices into graphs using the interactions of variables via a graph structure learning module and obtain the spatial-temporal graph node features via a temporal convolutional module. To obtain global graph-level representation, we design an "encoder-decoder"-based variational graph pooling module to create adaptive centroids for cluster assignments. Then, we combine GNNs and our proposed variational graph pooling layers for joint graph representation learning and graph coarsening, after which the graph is progressively coarsened to one node. Finally, a differentiable classifier uses this coarsened representation to obtain the final predicted class. Experiments on ten benchmark datasets showed that MTPool outperforms state-of-the-art strategies in the MTSC task.

Encapsulating powder ingredients into hydrogel with programmable release ability is highly demanded in many fields including food engineering, medical and healthcare fields. However, directly adding water-insoluble powders into pre-gel solution makes the mixture susceptible to clogging problems during processing, thus limiting the loading rate. To address this problem, a new way to encapsulate water-insoluble powder ingredients without addition of any organic solvent named bubble-assisted encapsulation method is developed in this study. The powders were firstly encapsulated in hydrogel bubbles and further dispersed by T-shaped microfluidic flow to form the core/shell-structured powder in hydrogel microcapsules (P/H microcapsules). The obtained P/H microcapsules had an exceptionally high loading rate of water-insoluble powders up to 94.76%. The P/H microcapsules were freeze-dried for long-term storage, and meanwhile, the as-prepared microcapsules were able to swell rapidly to soft state before use. Moreover, with the well-defined core–shell structure, the P/H microcapsules were endowed with dual release capabilities to external stimuli. The bubble-assisted encapsulation method that enables direct dense encapsulation of powder ingredients at a high loading rate appears promising for water-insoluble food or pharmaceutical ingredients delivery.

In this paper, we investigate the kinetic freeze-out properties in relativistic heavy ion collisions at different collision energies. We present a study of standard Boltzmann-Gibbs blast-wave (BGBW) fits and Tsallis blast-wave (TBW) fits performed on the transverse momentum spectra of identified hadrons produced in $\mathrm{Au}+\mathrm{Au}$ collisions at collision energies of $\sqrt{{s}_{\mathrm{NN}}}=7.7$--200 GeV at the Relativistic Heavy Ion Collider (RHIC), and in $\mathrm{Pb}+\mathrm{Pb}$ collisions at collision energies of $\sqrt{{s}_{\mathrm{NN}}}=2.76$ and 5.02 TeV at the Large Hadron Collider (LHC). The behavior of strange and multistrange particles is also investigated. We found that the TBW model describes data better than the BGBW one overall, and the contrast is more prominent as the collision energy increases as the degree of nonequilibrium of the produced system is found to increase. From TBW fits, the kinetic freeze-out temperature at the same centrality shows a weak dependence of collision energy between 7.7 and 39 GeV, while it decreases as collision energy continues to increase up to 5.02 TeV. The radial flow is found to be consistent with zero in peripheral collisions at RHIC energies but sizable at LHC energies and central collisions at all RHIC energies. We also observed that the strange hadrons, with higher temperature and similar radial flow, approach equilibrium more quickly from peripheral to central collisions than light hadrons. The dependence of temperature and flow velocity on nonequilibrium parameter ($q\ensuremath{-}1$) is characterized by two second-order polynomials. Both $a$ and $d\ensuremath{\xi}$ from the polynomials fit, related to the influence of the system bulk viscosity, increase toward lower RHIC energies.

Dielectric elastomer (DE) possesses attributes such as large deformation and fast response. As a typical DE actuating structure, the multilayered DE bending actuator (MDEBA) is lightweight and can actuate in relatively low voltage without a rigid frame and pre-stretch. These attributes arouse wide research interest in the MDEBA on the application of soft robots. However, due to its large deformation and nonlinear electromechanical dynamics, the control of MDEBA remains highly challenged. Considering the large bending deformation and gravity effect, we develop an electromechanical dynamic model-based control strategy, which can adaptively compensate for the parameter uncertainties during the actuation of MDEBA. Experimental results validate that this control strategy provides highly enhanced control performance compared to the proportional integral derivative (PID) controller. The electromechanical modeling method and dynamic control strategy may guide the further study of MDEBA, soft robots, and flexible devices.

In this paper, we develop the novel approach to design and fabricate dielectric elastomer (DE) actuator integrating with 3D printed flexible structures, demonstrating large deformation and multi-functionalities. This technique facilitates the combination of complex soft structures fused on the DE membrane without any extra adhesive. Based on the DE actuator, a soft gripper has been fabricated and characterized in terms of bending angle and blocked force. Finite element method (FEM) simulations precisely predict the electromechanical behaviors, guiding the design of the soft actuator. With optimal design, the finger-like soft actuator can generate large actuation with the bending angle about of 128 °. This study can guide the fabrication and modeling of highly designable and customized DE actuators, which are promising in the applications of soft robotics, flexible electronics, and medical devices.

We propose a novel chip combining co-flow and step emulsification for flexible on-line control of droplet generation. Through this technique, we obtain controllable uniformly sized water in oil droplets. The droplet diameter is controlled between 101 and 1550 μm and the generation frequency ranges from 0.32 to 100 Hz when using the new chip. Compared with conventional step emulsification, droplet dimension is reduced by more than 50% and throughput is increased up to a factor of 50 by using continuous phase co-flow within a certain range in the chip. We also simulate the effects of interfacial tension and flow velocities on emulsification. As continuous phase velocity increases, co-flow gradually replaces the Laplace pressure difference as the driving mechanism in step emulsification. Compared with step-emulsification, the effects of interfacial tension on droplet size and generation frequency greatly change when continuous phase co-flow is added. Co-flow causes both droplet diameter and generation frequency to increase with increasing dispersed phase velocity. Meanwhile, the driving mechanism changes from co-flow to Laplace pressure difference as the dispersed phase velocity increases, because of the increase in pinch-off distance. In addition, droplet generation changes from dripping to jetting as dispersed phase velocity increases. These effects of continuous phase co-flow on step emulsification are significant, and this technique can be easily used for tunable and high-throughput droplet production.

Fiber-reinforced thermosetting composites are of great significance in aerospace, marine, automotive, wind power, and civil engineering fields. They have outstanding advantages and can reduce weight and enhance performance, especially by replacing steel pieces. However, nonreversible cured deformation is an obstacle to the rapid development of these composite components. Studies in this field typically focus on the numerical prediction of the effects of cured deformation on composite components, which helps engineers design and modify the mold to compensate for deformation. In this review we discuss the latest achievements relating to cured deformation mechanisms, prediction models, and control strategies in fiber-reinforced material fields. In particular, different intrinsic and extrinsic factors that affect cured deformation are summarized and five main control strategies are proposed: die surface compensation, process optimization, structural optimization, tool-part contact optimization, and development of other methods. In addition, the effects of these factors on controlling deformation are compared. Unlike previous studies, this study integrates control strategies and the main mechanisms involved to achieve a more comprehensive view of cured deformation in thermosetting composites.

Ultra-relativistic heavy-ion collisions are expected to produce the strongest electromagnetic fields in the known Universe. These highly-Lorentz contracted fields can manifest themselves as linearly polarized quasi-real photons that can interact via the Breit-Wheeler process to produce lepton anti-lepton pairs. The energy and momentum distribution of the produced dileptons carry information about the strength and spatial distribution of the colliding fields. Recently it has been demonstrated that photons from these fields can interact even in heavy-ion collisions with hadronic overlap, providing a purely electromagnetic probe of the produced medium. In this review we discuss the recent theoretical progress and experimental advances for mapping the ultra-strong electromagnetic fields produced in heavy-ion collisions via measurement of the Breit-Wheeler process., updated, v2 was incorrect manuscript and metadata

Microcapillary film (MCF) is an extruded plastic film with an array of parallel microcapillaries (30-500 μm) and it has wide potential applications in bioanalytical techniques as a microfluidic platform. With different surface modification strategies, an MCF combines the advantages of its structure and modified chemical properties to realize various bioanalytical functions. In this review, we begin by introducing the manufacturing process of MCFs, common materials used to produce MCFs, surface treatment approaches of inner surfaces, and a signal detection and readout system of the MCF platform. Then, we summarize some typical applications of MCFs, particularly in protein chromatography, Escherichia coli detection for urinary tract infections, prostate-specific antigen detection for prostate cancer and multiplex immunoassays. Finally, future perspectives of MCFs in bioanalytical techniques are discussed.

Up to now, various approaches have been used to fabricate lignin-based epoxy thermosets by utilizing lignin or lignin-derivatives, but there is still lack of a simple, effective and environmental-friendly pathway for producing lignin-based epoxy resins from industrial lignin. In this work, a novel strategy - one-pot to synthesize phenolated lignin incorporated novolac epoxy networks (PLIENs) was proposed. As expected, PLIENs obtained from the novel route exhibited preferable mechanical and thermal properties compared with the epoxy resins which obtained from common route. Moreover, increasing the loading of lignin did not significantly deteriorate the thermal-mechanical performance of cured epoxy resins. However, the Tg of PLIENs was slightly lowered compared with conventional petroleum-based epoxy resins (DGEBA). Nonetheless, the flexural strength and storage modulus of PLIENs were higher than that of DGEBA. Especially, the char yield of PLIENs at 800 °C was up to 28.9%, much higher than that of DGEBA (only 6.9%), which indicated that lignin has a certain promoting effect on the flame retardancy of epoxy resins. This research provides a new insight for producing commercially viable lignin-based epoxy thermosets.

A Tesla valve is a passive check valve but with no-moving parts. The unique diode nature of Tesla valves makes them attractive for fluid control in many engineering fields, such as microfluidic systems and hydrogen fuel systems. The effectiveness of a single-stage Tesla valve can be modified by changing its geometric parameters. In this study, four groups of Tesla valves by changing the angle between 45° and 90° are examined. Numerical and mathematical methods are used to compare the diode characteristics of the four groups of Tesla valves, and proper orthogonal decomposition is applied to analyze the main flow fields. Of particular interest is that the diode property is induced by separation bubbles, with those near the left junction of the Tesla valve providing the main control mechanism for the fluid flow. For the forward flow, the main bubble pushes the fluid into the straight channel, while for the reverse flow, the main bubble blocks the outlet of the Tesla valve, making it difficult for fluid to flow out. Notably, our findings suggest that the diode performance of Tesla valves is optimal at θ = 70–80°. The results presented in this paper identify the functional relationship between the angle of the Tesla valve, Reynolds number, and diodicity, and suggest strategies for the optimal design and performance predictions of Tesla valves.

We present STAR measurements of strange hadron (KS0, Λ, Λ¯, Ξ−, Ξ¯+, Ω−, Ω¯+, and ϕ) production at midrapidity (|y

Rotor stator interaction (RSI) is an important phenomenon influencing performances in the pump, turbine, and compressor. In this paper, the correlation-based transition model is used to study the RSI phenomenon between a translational cascade of airfoils and a flat plat. A comparison was made between computational results and experimental results. The computational boundary layer velocity is in reasonable agreement with the experimental velocity. The thickness of boundary layer decreases as the RSI frequency increases and it increases as the fluid flows downstream. The spectral plots of velocity fluctuations at leading edge x/c = 2 under RSI partial flow condition f = 20 Hz and f = 30 Hz are dominated by a narrowband component. RSI frequency mainly affects the turbulence intensity in the freestream region. However, it has little influence on the turbulence intensity of boundary layer near the wall. A secondary vortex is induced by the wake&ndash, boundary layer interaction and it leads to the formation of a thickened laminar boundary layer. The negative-vorticity wake also facilitates the formation of a thickened boundary layer while the positive-vorticity wake has a similar effect, like a calmed region which makes the boundary layer thinner.

The deep sea remains the largest unknown territory on Earth because it is so difficult to explore1–4. Owing to the extremely high pressure in the deep sea, rigid vessels5–7 and pressure-compensation systems8–10 are typically required to protect mechatronic systems. However, deep-sea creatures that lack bulky or heavy pressure-tolerant systems can thrive at extreme depths11–17. Here, inspired by the structure of a deep-sea snailfish15, we develop an untethered soft robot for deep-sea exploration, with onboard power, control and actuation protected from pressure by integrating electronics in a silicone matrix. This self-powered robot eliminates the requirement for any rigid vessel. To reduce shear stress at the interfaces between electronic components, we decentralize the electronics by increasing the distance between components or separating them from the printed circuit board. Careful design of the dielectric elastomer material used for the robot’s flapping fins allowed the robot to be actuated successfully in a field test in the Mariana Trench down to a depth of 10,900 metres and to swim freely in the South China Sea at a depth of 3,224 metres. We validate the pressure resilience of the electronic components and soft actuators through systematic experiments and theoretical analyses. Our work highlights the potential of designing soft, lightweight devices for use in extreme conditions. A free-swimming soft robot inspired by deep-sea creatures, with artificial muscle, power and control electronics spread across a polymer matrix, successfully adapts to high pressure and operates in the deep ocean.

Author(s): Adam, J; Adamczyk, L; Adams, JR; Adkins, JK; Agakishiev, G; Aggarwal, MM; Ahammed, Z; Alekseev, I; Anderson, DM; Aparin, A; Aschenauer, EC; Ashraf, MU; Atetalla, FG; Attri, A; Averichev, GS; Bairathi, V; Barish, K; Behera, A; Bellwied, R; Bhasin, A; Bielcik, J; Bielcikova, J; Bland, LC; Bordyuzhin, IG; Brandenburg, JD; Brandin, AV; Butterworth, J; Caines, H; Calderon De La Barca Sanchez, M; Cebra, D; Chakaberia, I; Chaloupka, P; Chan, BK; Chang, FH; Chang, Z; Chankova-Bunzarova, N; Chatterjee, A; Chen, D; Chen, JH; Chen, X; Chen, Z; Cheng, J; Cherney, M; Chevalier, M; Choudhury, S; Christie, W; Crawford, HJ; Csanad, M; Daugherity, M; Dedovich, TG; Deppner, IM; Derevschikov, AA; Didenko, L; Dong, X; Drachenberg, JL; Dunlop, JC; Edmonds, T; Elsey, N; Engelage, J; Eppley, G; Esha, R; Esumi, S; Evdokimov, O; Ewigleben, A; Eyser, O; Fatemi, R; Fazio, S; Federic, P; Fedorisin, J; Feng, CJ; Feng, Y; Filip, P; Finch, E; Fisyak, Y; Francisco, A; Fulek, L; Gagliardi, CA; Galatyuk, T; Geurts, F; Gibson, A; Gopal, K; Grosnick, D; Guryn, W; Hamad, AI; Hamed, A | Abstract: Particle production sensitive to nonfactorizable and nonperturbative processes that contribute to the underlying event associated with a high transverse momentum (pT) jet in proton+proton collisions at s=200 GeV is studied with the STAR detector. Each event is divided into three regions based on the azimuthal angle with respect to the highest-pT jet direction: In the leading jet direction ("Toward"), opposite to the leading jet ("Away"), and perpendicular to the leading jet ("Transverse"). In the Transverse region, the average charged particle density is found to be between 0.4 and 0.6 and the mean transverse momentum

This study is concerned with comparing raw dairy wastewater (DWW) with blue-green medium (BG11 medium) for biofuel production. Three microalgae strains (Chlorella sp., Scenedesmus sp., and Chlorella zofingiensis) were cultured in tubular bubble column photobioreactors with two media separately. After 8 days of cultivation, DWW was demonstrated to be more suitable medium for microalgae biomass and lipid production than BG11 medium. The biomass and lipid produced within wastewater provided suitable feedstocks for anaerobic digestion and biodiesel conversion. Nutrients in wastewater were efficiently removed (>90% total nitrogen removal, approximately 100% ammonia removal, and >85% total phosphorus removal) during this process.

Terrace-based microfluidic devices are currently used to prepare highly monodisperse micro-droplets. Droplets are generated due to the spontaneous pressure drop induced by the Laplace pressure, and so the flow rate of a dispersed phase has little effect on droplet size. As a result, control over the droplet is limited once a step emulsification device has been fabricated. In this work, a terrace model was established to study the effect of the wall contact angle on droplet size based on computational fluid dynamics simulations. The results for contact angles from 140° to 180° show that a lower contact angle induces wall-wetting, increasing the droplet size. The Laplace pressure equations for droplet generation were determined based on combining pressure change curves with theoretical analyses, to provide a theoretical basis for controlling and handling droplets generated through step emulsification.

A one-pot method to synthesize demethylated-phenolated lignin (DPL) and demethylated-phenolated lignin-based epoxy resin (DPLINP) using phenol as a phenolic reagent and polymerization inhibitor was proposed in this study. This method avoids the occurrence of polycondensation caused by demethylation and simplifies the synthesis of lignin-based epoxy resins. Phenolated lignin (PL)-based epoxy resin (PLINP) and demethylated lignin (DL)-based epoxy resin (DLINP) were prepared to investigate the effects of different modification methods on the resulting lignin and epoxy resin. The results of 1H nuclear magnetic resonance (NMR), Fourier transform infrared, and gel permeation chromatography analyses indicated that the introduction of phenol could significantly reduce the occurrence of polycondensation while also decreasing the molecular weight and increasing the content of phenolic hydroxyl in DPL compared with DL and PL. 2D heteronuclear single quantum coherence NMR analysis was used to further investigate the structural changes of lignin during the modification process. The results obtained via dynamic mechanical analysis, flexural test, and impact test demonstrated that demethylated-phenolated lignin-based epoxy network (DPLIEN) possessed an improved cross-linking density, glass transition temperature, and mechanical performance compared with all other epoxy resins. Moreover, the polycondensation of DL caused by demethylation deteriorated the mechanical performance of demethylated lignin-based epoxy network (DLIEN). The thermal stability of DPLIEN was decreased compared with phenolated lignin-based epoxy network (PLIEN), as the removal of methoxy groups may have reduced the protective char layer formation in DPLIEN. This study provides a novel method for the modification of lignin and synthesis of lignin-based epoxy resins.

In this study, the effects of both limited oxygen gradient supplies (0, 0.1–0.3, and 0.3–0.5 mg/L) and nitrate as electron acceptors and an external carbon source in the anoxic phase on nitrogen and phosphorus removal and microbial community structures were investigated. The results demonstrated that more than 90% of the NO3–-N and P removal efficiencies were achieved under limited oxygen conditions (0.1–0.5 mg/L). Improved NH4+-N removal and anaerobic COD uptake were achieved under conditions of high oxygen concentrations. The genera of Dechloromonas (DPAOs) and norank _ f _ Bacteroidetes BD2–2 (PAOs) performed P removal without and with oxygen in the reactor, respectively. The genera of Defluviicoccus and Candidatus Competibacter (GAOs) were mainly responsible for NO3–-N removal in all phases. It indicated that the GAOs and PAOs were responsible for NO3–-N and P removal with a relationship of cooperation besides the competition to carbon source. When there was an external COD in the anoxic phase, the COD and NO3–-N could be removed by the genera of Azospira and Thauera thanks to the heterotrophic denitrification. However, the P removal efficiency decreased as the vicious circle that external COD deteriorated the anoxic P removal and polyhydroxyalkanoates (PHAs) consumption, leading to the decrease of the following anaerobic P release and PHAs synthesis, and more remaining COD. Thus, the anaerobic-anoxic-nitrifying (A2N) process was suggested to be a promising approach for nutrition removal, considering the negative effects of anoxic external COD. Moreover, the formation of granular sludge was promoted under limited oxygen conditions.

A novel testing machine, integrating plastic vibration processing with molding, based on a multipass rheometer, was used to investigate the effect of the complex force field on plasticizati...

This work proposes a novel method for the semi-quantitative determination of hydrogen peroxide (H2O2) in routine applications. Potassium iodide (KI) and starch are adopted as chromogenic reagents, while microcapillary films (MCFs) are employed as the reaction platform. An innovative loading method, including filling, gelatinization, and freeze-drying of reagents, is established to create a solid porous medium inside the MCF matrix for immobilizing the reagents. The porous medium has sufficient specific surface area and rapid rehydration for reaction detection. To verify the feasibility of this new method, two kinds of test strips were fabricated in the present investigation: a colorimetric strip and four-section grading test strip. Results showed that the standard colorimetric strip could detect H2O2 residue with concentrations of 0.02–0.1 wt% with a testing time of 120 s. Meanwhile, using the four-section grading test strip, the H2O2 residue concentration was determined simply by counting the number of colored sections with the naked eye. H2O2 concentrations of 0–0.12 wt% were divided into five grades by the grading test strips, with a testing time of 45 s. Compared with traditional colorimetric methods, this grading method provides a more intuitive and understandable result for users. Furthermore, it provides a new way to involve people suffering from color weakness or blindness in the relevant research community.

Emulsification is a key step in many processes for the production and functionalization of dispersed liquid systems. Here, we report a versatile and robust device that generates monodisperse milliemulsions by step-emulsification. In contrast to the conventional design in which each channel is physically separated, we use a shallow plateau sandwiched between two parallel glass strips to connect all channels in a microcapillary film (MCF) before emerging in a deep reservoir. Because of the open plateau that connects different channels, the flow tips from neighboring channels may get immediately in contact with each other; this interaction may lead to the relative movement and deformation of the flow tips, to repulsion or even coalescence, enabling droplet generations from different channels to synchronize. By simply tuning the interaction, we achieve Janus droplets, drops of fluids mixed at different ratios and mixed drops of different compositions. The in situ generation of droplets with excellent control is essential for various applications.

This paper studies the influence of added mass, centrifugal force and hydraulic load on natural frequencies of a Reactor Coolant Pump (RCP) impeller. A series of comparative studies under different conditions were carried out on a modal test bench and a simulation platform. Modal analysis of a full-scale RCP impeller was conducted by simulation, and an improved design of impeller was proposed to prevent hydraulic resonance. These results indicated that hydraulic load increases natural frequencies of the impeller. While the centrifugal force slightly reduces them, but it is negligible. Because the distribution of hydraulic load has an effect to natural frequencies, a solution of cutting inlet edges of blades can be used to increase the natural frequency that may cause hydraulic resonance. In summary, our research shows that both added mass and hydraulic load have a significant influence on natural frequencies of the RCP impeller, and redistributing the hydraulic load can alter natural frequencies of the impeller.

The double-slit experiment has become a classic thought experiment for its clarity in expressing the central puzzle of quantum mechanics—wave-particle complementarity. Such wave-particle duality continues to be challenged and investigated in a broad range of entities with electrons, neutrons, helium atoms, C60 fullerenes, Bose-Einstein condensates, and biological molecules. In this Rapid Communication, we present a double-slit scenario at Fermi scale with new entities—coherent photon products in heavy-ion collisions. Virtual photons from the electromagnetic fields of relativistic heavy ions can fluctuate to quark-antiquark pairs, scatter off a target nucleus, and emerge as vector mesons. The two colliding nuclei can take turns to act as targets, forming a double-slit interference pattern. Furthermore, the “which-way” information can be partially solved using sufficiently-high multiplicity heavy-ion collisions so that the reaction plane can be determined, which demonstrates the complementary principle, a key concept of quantum mechanics.

We report new STAR measurements of the single-spin asymmetries $A_L$ for $W^+$ and $W^-$ bosons produced in polarized proton--proton collisions at $\sqrt{s}$ = 510 GeV as a function of the decay-positron and decay-electron pseudorapidity. The data were obtained in 2013 and correspond to an integrated luminosity of 250 pb$^{-1}$. The results are combined with previous results obtained with 86 pb$^{-1}$. A comparison with theoretical expectations based on polarized lepton-nucleon deep-inelastic scattering and prior polarized proton--proton data suggests a difference between the $\bar{u}$ and $\bar{d}$ quark helicity distributions for $0.05 < x < 0.25$. In addition, we report new results for the double-spin asymmetries $A_{LL}$ for $W^\pm$, as well as $A_L$ for $Z/\gamma^*$ production and subsequent decay into electron--positron pairs.

In order to assess viability of microalgae cultivation using unsterilized dairy-derived liquid digestate (DLD) for simultaneous biofuels feedstock production and contaminant removal, four DLD concentrations (25%, 50%, 75% and 100%) were used to grow Chlorella vulgaris in batch photobioreactors (PBRs). The 25% DLD was an ideal alternative medium in that high growth rate (0.69 d−1), high lipid productivity (112.9 mg L−1 d−1) as well as high nutrient removal were attained. The high DLD concentration caused inhibition of microalgal growth, where COD was more inhibitive than ammonium. The presence of bacteria did not influence microalgae production because of limited growth. Microalgal growth reduced the richness and diversity of bacterial community. Furthermore, the species of Bacteroidetes, Candidatus Saccharibacteria, and Chlamydiae rather than Proteobacteria benefited microalgal-bacterial symbiosis. These findings contribute to better application of microalgal-bacterial system for large-scale microalgae cultivation as well as environmental sustainability.

Author(s): Adam, J; Adamczyk, L; Adams, JR; Adkins, JK; Agakishiev, G; Aggarwal, MM; Ahammed, Z; Alekseev, I; Anderson, DM; Aoyama, R; Aparin, A; Arkhipkin, D; Aschenauer, EC; Ashraf, MU; Atetalla, F; Attri, A; Averichev, GS; Bairathi, V; Barish, K; Bassill, AJ; Behera, A; Bellwied, R; Bhasin, A; Bhati, AK; Bielcik, J; Bielcikova, J; Bland, LC; Bordyuzhin, IG; Brandenburg, JD; Brandin, AV; Bryslawskyj, J; Bunzarov, I; Butterworth, J; Caines, H; Calderon De La Barca Sanchez, M; Cebra, D; Chakaberia, I; Chaloupka, P; Chan, BK; Chang, FH; Chang, Z; Chankova-Bunzarova, N; Chatterjee, A; Chattopadhyay, S; Chen, JH; Chen, X; Cheng, J; Cherney, M; Christie, W; Crawford, HJ; Csanad, M; Das, S; Dedovich, TG; Deppner, IM; Derevschikov, AA; Didenko, L; Dilks, C; Dong, X; Drachenberg, JL; Dunlop, JC; Edmonds, T; Elsey, N; Engelage, J; Eppley, G; Esha, R; Esumi, S; Evdokimov, O; Ewigleben, J; Eyser, O; Fatemi, R; Fazio, S; Federic, P; Fedorisin, J; Feng, Y; Filip, P; Finch, E; Fisyak, Y; Fulek, L; Gagliardi, CA; Galatyuk, T; Geurts, F; Gibson, A; Grosnick, D; Gupta, A; Guryn, W | Abstract: We report the energy dependence of mid-rapidity (anti-)deuteron production in Au+Au collisions at sNN=7.7, 11.5, 14.5, 19.6, 27, 39, 62.4, and 200 GeV, measured by the STAR experiment at the BNL Relativistic Heavy Ion Collider. The yield of deuterons is found to be well described by the thermal model. The collision energy, centrality, and transverse momentum dependence of the coalescence parameter B2 are discussed. We find that the values of B2 for antideuterons are systematically lower than those for deuterons, indicating that the correlation volume of antibaryons is larger than that of baryons at sNN from 19.6 to 39 GeV. In addition, values of B2 are found to vary with collision energy and show a broad minimum around sNN=20-40 GeV, which might imply a change of the equation of state of the medium in these collisions.